Effective decision-making is central to the success of any business. As information age technology matures, electronic data collection has become a widespread practice for assisting in the decision-making process. A typical business enterprise maintains a wide variety of data from various sources, and the data may be in different formats. In recent years, various tools have been developed to help businesses access such a hodgepodge of data. Thus, for many businesses, the volume of available information has reached an all-time high.
Given that it is impossible for one person to comprehend such available information in its totality, other tools have been developed to help decision-makers sift through the available information during the decision-making process. For example, the widely available Structured Query Language (“SQL”) has become a popular tool for pulling appropriate information out of a database.
Although SQL is powerful, a user must grasp predicate calculus, database theory, and an understanding of the database layout to use it effectively. So, a user must typically undergo a considerable amount of training before the user can even begin to use SQL, and truly effective use of SQL requires a seasoned database expert.
Often, those users who most need access to the data are skilled at making decisions but are unable to acquire the training and experience necessary to effectively use SQL. For example, a sales manager may be devoted to attracting and keeping clients and not have the time or desire to learn the technical details of how the company's database works.
Accordingly, SQL effectively serves as a barrier between the decision-maker and the information in the database. One way to overcome such a barrier is to provide a blanket report to all users, who must then peruse the report to find the portions that apply to them. However, such an approach places the user at the mercy of the group who generates the report. The report may have too much or too little information to be effective.
To address SQL's problems, other tools have emerged. For example, a technique called “query by example” has been put forth as a user-friendly tool for extracting information from a database. In a query by example system, the user is presented with a representation of columns of tables in the database and can choose which of the columns are desired. The user can further limit the information by specifying criteria, such as dates and other values.